The international competition challenged the teams to develop short-term traffic forecasting models to predict the five-minute average speed on a road section along Chang’an North Road in Xi’an, China. The dataset is provided by DiDi Chuxing Technology Co., a Chinese ride-sharing company through Gaia Open Data Initiative. The submissions are evaluated based on prediction accuracy (50%), degree on novelty (25%), quality of the code (10%), and quality of the presentation (15%).

With the highest prediction accuracy, ITS-Irvine teams ranked #1 in the pre-selection stage and finished top after the final presentation at TRB 2019 Workshop 1058 “Big Data Without Machine Learning Is Just Lots of Data: A Guided Tour to Big Data and Machine Learning”.